ML4H Process and Content Management System

A unified modelling framework to address the problem of conceptual mapping and semantic interoperability of product requirements of AI/ML based medical devices among various stakeholders including software developers, quality managers, medical professionals and notified bodies.


This project aims at the design and development of a process and content management system(PCMS) for regulatory good machine learning practice guidelines(GMLP). The PCM system can potentially serve as a workflow utility or tool for the healthcare AI product developers, manufactiurers and regualtors and can guide them on how to efficiently and optimally adopt the regulatory GMLPs in reducing the complexity of the requirements analysis and conformity assessment workflows.


  • To develop an ontology database

  • To define processes for database content update


    Collaboration resources

    You are welcome to inquire about the work stream and opporunities for collaboration directly with the work stream team.

    • General contact Christian Johner, / Pradeep Balachandran,


    Regular meetings for this work stream take place at the below coordinates.


    You can subsbscribe to the work stream mailing list to receive updates and join the asynchronous group chat.

    • Group chat
    • Mailing list


    We use different tools in our remote work. They include shared documents, github projects for code as well as task tracking and a collaborative whiteboard for ideation. You can request access via the below links.

    • Shared drive
    • Github project
    • Collaborative whiteboard

    You can find more information about the way we usually carry out our work remotely in teams here.


    Important reference material

    This is a list of related work and resources relevant for this work stream. It comprises resources the work stream contributors consider good practice.

    1. ITU/WHO
      Good practices for health applications of machine learning: Considerations for manufacturers and regulators
      Johner, Christian, Balachandran, Pradeep, Oala, Luis, Lee, Aaron .Y., Leite, Alixandro Werneck, Murchison, Andrew, Lin, Anle, Molnar, Christoph, Rumball-Smith, Juliet, Baird, Pat, Goldschmidt, Peter. G., Quartarolo, Pierre, Xu, Shan, Piechottka, Sven, and Hornberger, Zack
      In Proceedings of the ITU/WHO Focus Group on Artificial Intelligence for Health (FG-AI4H) - Meeting K 2021